Abstract:
Understanding how the brain works means understanding how it functions in a rich sensory environment. Functional MRI provides us with a window into brain processes, but to interpret these measurements we need to understand what is signal and what is noise. Our approach was to explore the predictive power of simple linear techniques as a lower boundary on how much information is actually present in the signal. To our surprise linear methods seemed to have performed fairly well, but the key improvement was temporal and spatial averaging that may indicate that a higher spatial resolution does not actually provide more information about the brain state. Alternatively, spatial averaging may have simply acted as a regularization parameter given the limited nature of the data set.
Denis Chigirev is a physics graduate student at Princeton University. After graduation from Physical Technical High School #566 in St. Petersburg, Russia, Denis won a top prize at International Physics Olympiad and was awarded a scholarship to study at the University of Chicago. He then spent a year at Trinity College, Cambridge University, before joining Princeton as a graduate student. There he became interested in problems at the intersection of physics, biology and computer science. He is currently finishing his dissertation.
Greg Stephens received Ph.D. in Physics (Cosmology) from the University of Maryland. He currently holds a joint postdoctoral position between the Physics Department and the Center for Brain, Mind and Behavior at Princeton University. Denis and Greg are also active members of the Biophysics Theory group headed by Bill Bialek.
Princeton's EBC entries are the result of collaboration among students, postdocs, & faculty from multiple departments at Princeton, including Psychology, Physics, Computer Science, Electrical Engineering, and Applied Mathematics. Over the course of the competition, members of the EBC team met on a regular basis to discuss methods & share code. The team was comprised of the following researchers (in alphabetical order): David Blei, Eugene Brevdo, Ronald Bryan, Melissa Carroll, Denis Chigirev, Greg Detre, Andrew Engell, Shannon Hughes, Christopher Moore, Ehren Newman, Ken Norman, Vaidehi Natu, Susan Robison, Greg Stephens, and Matt Weber. The team was coordinated by Greg Detre (a Psychology graduate student) and supervised by Ken Norman (a Psychology faculty member).
